Richard L. Willham

Imputing Input Characteristic Values from Optimal Commercial Breed or Variety Choice Decisions

Previous Input Characteristics Models (ICMs) are modified and extended to allow the economic values of individual genetic characteristics to be imputed, even when those characteristics are acquired in largely inseparable bundles such as in the animal breed or plant variety decision of commercial producers. Through analysis of the commercial breed selection decision for a representative beef producer, the extended ICM is shown to generally be more flexible, with less restrictive data requirements for estimation, than prior ICMs. Additional modifications of the extended ICM method of analysis are suggested to further enhance and broaden its applicability.

AVOIDANCE LEARNING IN SWINE

The purpose of the present study was to develop a measure of learning in swine that could be mzde rapidly and would be sensitive to individual differences, so that the genetic effects of irradiation on this measure of learning could be investigated. Pxevious learning studies with swine (Hafez, et al., 1962) used procedures not amenable to testing the large numbers of Ss necessary for genetic analysis. Therefore, avoidance learning, typified by the work of Solomon (1953) with dogs and Mowrer (1946) with rats, was chosen since a response indicative of learning could be obtained in a relatively few trials of a short, near constant length. The performance of swine was tested in 40 trials under three different spacings: consecutively (40 X 1 ), 20 per day (20 X 2 ) , and 10 per day (10 X 4 ) . Although spacing would be expected to increase performance, more Ss could be tested under massed training. If the latter approached spaced training in sensitivity to individual differences, it would be preferable. Sensitivity to individual differences was defined as maximum when the average percentage of avoidances for a set of trials was 50%, since the variance of binomial data is maximum when p = q = 1/2.

Sperm production in swine after exposure to x-irradiation.

The number of sperm per collection was followed for one year in swine exposed to 0, 300, 600, and 900 r of radiation directed to the testicles. The general response pattern in swine conforms to that outlined for other mammals. About 60 days has been estimated as the interval from primary spermatocyte to sperm in the ejaculate. These data indicate that the general recovery pattern, as measured by sperm number per collection between 70 and 300 days, is linearly related to dose on a logarithmic plot. This suggests that recovery is a function of the number of surviving spermatogonia. The length of time required for recovery to fertility appears to be longer in swine than in mice.

The Impact of Alternative Objectives on Feedlot Rations for Beef Steers

The specification of an objective receives little attention in most agricultural production analyses. Despite general agreement among agricultural economists that few, if any, farmers are motivated exclusively by magnitude of profits, it is common simply to assume an objective of profit maximization. (Anderson, Dillon, Hardaker; Heady and Dillon). Use of this objective is sufficient for some analyses. For other analyses, however, the observed diversity of production practices makes this simple approach inappropriate. Beef production falls into the latter category. Even if we ignore beef marketed as mature animals from the culling of breeding herds, the diversity of production practices is obvious. A 20,000-head commercial feedlot manager on the Texas plains and an Iowa farmer feeding 100 head per year do not operate similarly and probably are not motivated by the same objectives. We attempt to quantify some of the objectives that are relevant for various groups of beef producers and to analyze the impact of these alternative objectives on beef production strategies. Five alternative objectives are defined for the feeding of a roughage (corn silage) and a corn-grain-based concentrate to beef steers to produce carcass weight gain. Additionally, using a fixed initial age and carcass weight (196 kg) and a fixed final carcass weight (295 kg), each objective is evaluated for a specific gain or over a fixed region of the response surface (see Melton). The assumption of a fixed slaughter weight is generally consistent with production of animals of a fixed U.S. Department of Agriculture (USDA) quality grade. It is appropriate to apply the analyses to carcass weight gain because the lower digestibility of roughages causes a greater portion of live weight to be undigested feed rather than beef.

A time-dependent bioeconomic model of commercial beef breed choices

Abstract The breed choice decision requires simultaneous consideration of both economic and physical relationships in light of the multi-year, multi-product nature of commerical cow-calf production. To accomplish this a time-dependent bioeconomic model of cow-calf production was developed in which both physical output-input relationships and production decisions are expressed in terms of cow age and stage of production. The breed choice and optimal herd distribution (culling age and proportion by age) decisions are then cast within the economic framework of maximizing net returns per unit of nutrient resource derived from a fixed land area. The resulting bioeconomic model is easily solved, as illustrated by an empirical example evaluating 16 alternative breed choices for a representative West Texas ranch. Results indicate a marked economic preference for smaller, higher productivity animals, such as Sahiwal. Conversely, large, slow maturing breeds with marginal reproductive capacity, such as Charolais, are least profitable for the fixed resource area defined.

IMPUTING CHARACTERISTIC VALUES OF AGRICULTURAL "SEED-STOCK"

Statistical methods of regression and mathematical (linear) programming are employed to combine principles of economics and genetics in a conceptual, multi-step, model of valuation for biotechnical change. The resulting model has the capacity to estimate the value of changes in specific characteristics for specific production environments, whether those changes are accomplished by traditional plant and animal breeding methods or by genetic engineering. The application of the model is illustrated with an example of commercial cow-calf production under conditions typical of the Texas Panhandle using a total of 32 breed groups. KEy WORDs: Biotechnical change, characteristic economic values, regression, mathematical programming